Atrial fibrillation (AF) is a major global health problem; in fact, unrecognized and untreated AF can lead to stroke and other adverse cardiac outcomes. The long-term goal of this research is to use mHealth cardiac monitoring technology to detect the presence of recurrent AF and improve self-management behaviors and patient outcomes. A total of 300 subjects with a prior history of AF (treated for AF in the last 30 days) will be enrolled. Subjects will be randomized in equal numbers to receive the iHEART intervention, receiving an iPhone(R) equipped with ECG monitoring capabilities and educational text messaging (n=150), or usual cardiac care (control group) (n=150) for 6 months. The study aims are to: Aim 1: Examine the efficacy of mHealth ECG technology (iHEART intervention) on the detection and treatment of recurrent AF as compared to usual cardiac care (control group). Aim 2: Evaluate the quality-adjusted life-years (QALYs) in those in the iHEART intervention as compared to the control group between baseline and 6 months. Aim 3: Determine the impact of behavior altering, motivational text messages on chronic cardiovascular conditions (e.g., hypertension, diabetes) and AF knowledge over 6 months. In addition to receiving usual cardiac care, those randomized to the iHEART intervention group will record a single channel ECG strip daily or in the setting of symptoms which can be sent via rapid cellular transmission to providers and the study team. Patients in the iHEART intervention will also receive behavior altering, motivational text messages three times a week. The detection rate for recurrent AF and subsequent treatments aimed at AF management over the 6-month study period in each of the groups will be determined. In addition, the Atrial Fibrillation Effect on QualiTy-of-life (AFEQT), European Quality of Life Scale (EQ5D), AF Knowledge Scale, and Canadian Cardiovascular Society Severity in Atrial Fibrillation (CSS-AF) questionnaires will be administered to both groups at baseline and 6 months to assess differences in QoL, QALYs, and AF knowledge. In Aim 1, the difference in proportions of AF detected between both groups will be performed using multivariate Poisson regression. We will apply a Cox proportional hazard model to examine and test the difference in the time-to-treatment between the groups with the adjustment for other potential confounders. In Aim 2, we will compare QALYs, QoL, and CCS-SAF scores between the iHEART intervention group and the control group using a two-sided t-test and multivariate linear regression models. In Aim 3, the effect of text messaging on cardiac outcomes and AF knowledge will be determined by a two-sided t-test and a linear mixed model (growth model). This project may change existing guidelines for how ECG monitoring and patient education are approached and lay the foundation for using mHealth interventions aimed at improving health promotion, QoL, and disease prevention.